September 19, 2013

Teaching computers to see — by learning to see like computers


By translating images into the language spoken by object-recognition systems, then translating them back, researchers hope to explain the systems’ failures.

Object-recognition systems — software that tries to identify objects in digital images — typically rely on machine learning. They comb through databases of previously labeled images and look for combinations of visual features that seem to correlate with particular objects. Then, when presented with a new image, they try to determine whether it contains one of the previously identified combinations of features.